Place
Room GC 101, Graduate Centre, Queen Mary University of London, Mile End Road, London E1 4NS. Information on how to access the school can be found at http://www.eecs.qmul.ac.uk/contact-us/.

Speaker
Ken Déguernel

Title
Learning of Musical Structures in the Context of Improvisation

Abstract
This work is part of the "Creative Dynamics of Improvised Interaction" project that aims at creating digital musical agents able to listen, learn and interact with human performers to generate creative improvisations. The aim of this work is to create a system able to learn the dependencies between several dimensions (e.g. pitch, harmony, rhythm…), take into account the form of music upon several levels of organisation (e.g. beat, measure, section…), and use this information to generate more creative and more artistically credible improvisations. We first present a system combining interpolated probabilistic models with a factor oracle. The probabilistic models are trained on a corpus and provide information on the correlation between dimensions and are used to guide the navigation in the factor oracle that ensure a logical improvisation. The improvisations are therefore generated in a way where the intuition of a context is enriched with multidimensional knowledge. We then introduce a system creating multidimensional improvisations based on interactivity between dimensions via message passing through a cluster graph. The communications infer some anticipatory behaviour on each dimension now influenced by the others, generating consistent multidimensional improvisations. Finally, we propose a method taking into account the form of a tune upon several levels of organisation to guide the music generation process. Phrase structure grammar are used to represent a hierarchical analysis of a chord progression and this multi-level structure is then used to enrich the possibilities of guided machine improvisation.

Bio
Ken Déguernel is a Ph.D. student in computer music, co-supervised by Emmanuel Vincent (Inria) and Gérard Assayag (IRCAM). He holds a master’s degree in theoretical computer science from the University of Rouen and a master’s degree in acoustic, signal processing, and informatics applied to music from IRCAM. His research interests include music informatics, formal language theory, automata and semigroups theory, probabilistic models and musicology. In particular, his work focuses on the understanding, the analysis and the modelling of the creative processes employed by musicians during improvisations in different contexts and different styles.